Machine vision is often used in industry in addition to or in lieu of human vision for a variety of applications. One such application is product inspection. During product inspection, a light source uses one or more lighting techniques to illuminate features of a unit under test (UUT) while a camera captures images of those features. Signal processing hardware and software are then used to analyze these images and to identify defects (e.g., cosmetic defects) on the UUT.
A common lighting technique for machine vision is brightfield illumination. Under brightfield illumination, light is directed at a UUT and is reflected back toward a lens of a camera. Software then analyzes abnormal characteristics (e.g., dark spots illustrating attenuation in the light reflected at the camera lens) in images of the UUT taken by the camera to identify, for example, defects in the UUT. However, using brightfield illumination to highlight curved features of a UUT poses several challenges. For example, typical brightfield sources often leave hotspots or saturated areas where the illumination and part geometry of the UUT interact on curved features to reflect more light to the camera from some regions and less from others. This becomes especially prevalent as the surface finish of the curved features becomes more specular than diffuse.